Objective To explore an artificial intelligence (AI)-based method for automated hand hygiene monitoring and to compare the effectiveness of three algorithms (UniFormerV2, TDN, C3D) in recognizing hand hygiene steps in surgical settings, thereby aiding hospital infection control. Methods From April to October 2024, we non-invasively collected 641 video recordings of healthcare staff performing hand hygiene at four-bay scrub sinks in two tertiary hospitals using overhead HD cameras. The dataset was annotated by five trained experts for model training and validation. Results Following training on 385 samples, internal validation (n=119) showed the C3D model achieved 81% accuracy, 87% recall, and an 83% F1-score. The TDN model achieved 93%, 91%, and 92% for the same metrics. The UniFormerV2 model outperformed both, with an accuracy, recall, and F1-score of 93%—an improvement of over 10 percentage points compared to traditional CNNs (TDN, C3D). It also achieved an 84% accuracy in external validation, demonstrating strong generalization. Conclusion The UniFormerV2 model is more accurate than CNN-based models for hand hygiene step recognition and shows robust performance in external validation. It presents a viable tool for healthcare facilities to enhance hand hygiene management, ultimately improving medical quality and patient safety.

Objective To explore the effect of remote ischemic preconditioning (RIPC) on preoperative heart rate variability in patients with heart valves. Methods Patients scheduled to undergo on-pump cardiac valve surgery in the Department of Cardiovascular Surgery, General Hospital of Northern Theater Command, between January and July 2022 were initially enrolled. Eligible patients were randomly assigned at a 1 : 1 ratio to either the RIPC group or the control group. Relevant indicators of heart rate variability [standard deviation of NN interval (SDNN), standard deviation of mean value of NN interval in every five minutes (SDANN), mean square root of difference between consecutive NN intervals (RMSSD), percentage of adjacent RR interval>50 ms (PNN50), low frequency (LF) component, high frequency (HF) component and LF/HF] at 8 hours in the morning on the surgical day between two groups were compared. Results A total of 118 patients were initially assessed. After screening, 58 patients were excluded, and 60 patients provided written informed consent and were enrolled in the trial, with 30 allocated to the RIPC group and 30 to the control group. Seven patients in the control group and 5 patients in the RIPC group were subsequently excluded due to missing heart rate variability data resulting from cancelled operations. Finally, 23 patients in the control group and 25 patients in the RIPC group were included in the analysis. There was no statistical difference in baseline characteristics between the two groups, and there was no significant difference in heart rate variability 24 hours before intervention (P>0.05). After the intervention measures were taken, the comparison of the results of heart rate variability at 8 hours on the day of operation showed that SDNN and SDANN of patients in the RIPC group were higher than those in the control group, with statistical differences (P<0.05). Conclusion RIPC can stabilize the preoperative heart rate variability of patients undergoing cardiac valve surgery.

Objective: To investigate the current status of refractive errors and insufficient hyperopia reserve in preschool children aged 3-6 years in Hefei and to analyze influencing factors, so as to provide a scientific basis for formulating targeted myopia prevention policies and comprehensive interventions. Methods: In May 2022, a stratified cluster random sampling method was used to select 897 preschool children from 8 kindergartens across four districts (Baohe, Yaohai, Shushan, and Economic and Technological Development Zone) in Hefei, and Children’s Visual Health related Behavior Assessment Scale was used to collect personal information and environmental factors. Pre and post cycloplegic refraction tests were conducted to assess insufficient hyperopic reserve and refractive development levels. Group comparisons were conducted using 2 test, t-test or analysis of variance. Multivariate regression analysis was performed to identify key factors influencing hyperopic reserve, axial length and spherical equivalent in preschool children. Results: The detection rates of refractive errors among preschool children were 6.8% for hyperopia, 1.6% for myopia, and 11.1% for astigmatism. Notably, the prevalence of myopia was significantly higher in boys (2.3%) than in girls (0.7%) ( χ 2=3.88, P <0.05). Additionally, 8.8% of the children exhibited insufficient hyperopic reserve. The results of multiple regression analysis showed that preschool children with high myopia in the father, high myopia in the mother, longer daily duration of near work, and longer daily electronic product use time had increased risks of axial growth ( β =0.12, 0.09, 0.15, 0.11), SE reduction ( β =-0.10, -0.07, -0.18, -0.13), and insufficient hyperopic reserve ( OR=1.87, 2.22, 1.40, 1.28) (P <0.05). While, preschool children with longer sleep time and daily outdoor activity duration had lower risks of axial growth ( β =-0.11, -0.10 ), SE reduction ( β =0.39, 0.51), and insufficient hyperopia reserve ( OR =0.54, 0.51) in preschool children ( P <0.05). Conclusions The rates of refractive errors and insufficient hyperopia reserve in preschool children in Hefei are relatively low, which are influenced by many factors. Parents, kindergartens and relevant departments should implement early vision monitoring and intervention for preschool children, and cultivate their scientific eye use habits.

Sinisan is a classical prescription developed and applied by ancient medical experts and it is first recorded in the Treatise on Cold Damage written by ZHANG Zhongjing in the Eastern Han Dynasty. Later physicians have modified this prescription based on this original one. The bibliometrics methods were used to analyze the key information and research trend of Sinisan. According to the inclusion and exclusion criteria， 69 pieces of effective data were extracted， involving 67 ancient traditional Chinese medicine （TCM） books. The results showed that the name， composition， and decocting methods of Sinisan in later generations were inherited from the original record in the Treatise on Cold Damage. The original plants of medicinal materials used in Sinisan are basically clear. We recommend Bupleuri Radix as the dried root of Bupleurem scorzonerifolium， Paeoniae Radix Alba as the dried root of Paeonia lactiflora， Aurantii Fructus as the dried fruit of Citrus aurantium， Glycyrrhizae Radix et Rhizoma as the dry root and rhizome of Glycyrrhiza uralensis. Raw materials of Bupleuri Radix and Paeoniae Radix Alba， Aurantii Fructus stir-fried with bran， and stir-fried Glycyrrhizae Radix et Rhizoma should be used for preparation of Sinisan. According to measurement system in the Han Dynasty， a bag of Sinisan is composed of 1.25 g Bupleuri Radix， 1.25 g Paeoniae Radix Alba， 1.25 g Aurantii Fructus， and 1.25 g Glycyrrhizae Radix et Rhizoma. The materials should be grounded into coarse powder and taken with a proper amount of rice soup， 3 times a day. Sinisan has the effects of regulating qi movement and harmonizing the liver and spleen. It can be used for treating reversal cold in limbs and cold damage. In modern clinical practice， Sinisan can be used to treat chronic gastritis， irritable bowel syndrome， and dyspepsia. The above research results provide scientific reference for the future research and development of Sinisan.

Qingfeitang， specialized in resolving phlegm to stop cough and producing fluid to moisten dryness， is a classic prescription inherited and developed by physicians of successive generations and has been included in the Catalogue of Ancient Classic Prescriptions （First Batch） published by the National Administration of Traditional Chinese Medicine （TCM） in 2018. Relevant ancient books data and modern literature were collected by bibliometrics to analyze the historic origin， formula composition， herb origin， preparation methods， processing methods， clinical effect， and indications of Qingfeitang. The key information of Qingfeitang was summarized to provide reference for the clinical application of the decoction. In this study， a total of 43 pieces of effective data on relevant ancient literature， including 35 ancient TCM books， were collected based on a systematic collation of relevant historic and modern literature. Results showed that "Qingfeitang" was originated from the "Renshen Qingfeitang" recorded in the Taiping Holy Prescriptions for Universal Relief from the Qing dynasty. The name of "Qinfeitang" was first recorded in the Yeshi Luyanfang written by YE Dalian in the Song dynasty. We suggested the modern dosage and usage of Qingfeitang as follows： "Scutellariae Radix of 5.60 g， Platycodon grandiflora， Poria， Tangerine， Fritillaria， and Cortex Mori of 3.73 g respectively， Angelicae Sinensis Radix， Asparagi Radix， Gardeniae Fructus， Armeniacae Semen Amarum， and Ophiopogonis Radix of 2.61 g respectively， Schisandra of 1 g， and Glycyrrhizae Radix et Rhizoma of 1.12 g， and they were taken 3 times daily. The above formula is recommended to be decocted with 400 mL of water， with 3.37 g ginger and 6 g jujubae fructus， to 320 mL， and taken after a meal， three times per day". Qingfeitang has the effect of resolving phlegm to stop cough and producing fluid to moisten dryness， specialized in treating cough， asthma， rash， and other symptoms in ancient times. Modern applications are mainly focused on the respiratory system， used for treating diseases such as bronchopneumonia and cough. The above research results provide a reference basis for the later development and research of Qingfeitang.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

Patients suffering from nerve injury often experience exacerbated pain responses and complain of memory deficits. The dorsal hippocampus (dHPC), a well-defined region responsible for learning and memory, displays maladaptive plasticity upon injury, which is assumed to underlie pain hypersensitivity and cognitive deficits. However, much attention has thus far been paid to intracellular mechanisms of plasticity rather than extracellular alterations that might trigger and facilitate intracellular changes. Emerging evidence has shown that nerve injury alters the microarchitecture of the extracellular matrix (ECM) and decreases ECM rigidity in the dHPC. Despite this, it remains elusive which element of the ECM in the dHPC is affected and how it contributes to neuropathic pain and comorbid cognitive deficits. Laminin, a key element of the ECM, consists of α-, β-, and γ-chains and has been implicated in several pathophysiological processes. Here, we showed that peripheral nerve injury downregulates laminin β1 (LAMB1) in the dHPC. Silencing of hippocampal LAMB1 exacerbates pain sensitivity and induces cognitive dysfunction. Further mechanistic analysis revealed that loss of hippocampal LAMB1 causes dysregulated Src/NR2A signaling cascades via interaction with integrin β1, leading to decreased Ca²⁺ levels in pyramidal neurons, which in turn orchestrates structural and functional plasticity and eventually results in exaggerated pain responses and cognitive deficits. In this study, we shed new light on the functional capability of hippocampal ECM LAMB1 in the modulation of neuropathic pain and comorbid cognitive deficits, and reveal a mechanism that conveys extracellular alterations to intracellular plasticity. Moreover, we identified hippocampal LAMB1/integrin β1 signaling as a potential therapeutic target for the treatment of neuropathic pain and related memory loss.
Animals ; Laminin/genetics* ; Hippocampus/metabolism* ; Neuralgia/metabolism* ; Cognitive Dysfunction/etiology* ; Male ; Peripheral Nerve Injuries/metabolism* ; Extracellular Matrix/metabolism* ; Integrin beta1/metabolism* ; Pyramidal Cells/metabolism* ; Signal Transduction

This study aimed to comprehensively examine the association of gallstones, cholecystectomy, and cancer risk. Multivariable logistic regressions were performed to estimate the observational associations of gallstones and cholecystectomy with cancer risk, using data from a nationwide cohort involving 239 799 participants. General and gender-specific two-sample Mendelian randomization (MR) analysis was further conducted to assess the causalities of the observed associations. Observationally, a history of gallstones without cholecystectomy was associated with a high risk of stomach cancer (adjusted odds ratio (aOR)=2.54, 95% confidence interval (CI) 1.50-4.28), liver and bile duct cancer (aOR=2.46, 95% CI 1.17-5.16), kidney cancer (aOR=2.04, 95% CI 1.05-3.94), and bladder cancer (aOR=2.23, 95% CI 1.01-5.13) in the general population, as well as cervical cancer (aOR=1.69, 95% CI 1.12-2.56) in women. Moreover, cholecystectomy was associated with high odds of stomach cancer (aOR=2.41, 95% CI 1.29-4.49), colorectal cancer (aOR=1.83, 95% CI 1.18-2.85), and cancer of liver and bile duct (aOR=2.58, 95% CI 1.11-6.02). MR analysis only supported the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer. This study added evidence to the causal effect of gallstones on stomach, liver and bile duct, kidney, and bladder cancer, highlighting the importance of cancer screening in individuals with gallstones.
Humans ; Mendelian Randomization Analysis ; Gallstones/complications* ; Female ; Male ; Cholecystectomy/statistics & numerical data* ; Middle Aged ; Risk Factors ; Aged ; Adult ; Neoplasms/etiology* ; Stomach Neoplasms/epidemiology*

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

OBJECTIVE: Pneumoconiosis, a lung disease caused by irreversible fibrosis, represents a significant public health burden. This study investigates the causal relationships between gut microbiota, gene methylation, gene expression, protein levels, and pneumoconiosis using a multi-omics approach and Mendelian randomization (MR). METHODS: We analyzed gut microbiota data from MiBioGen and Esteban et al. to assess their potential causal effects on pneumoconiosis subtypes (asbestosis, silicosis, and inorganic pneumoconiosis) using conventional and summary-data-based MR (SMR). Gene methylation and expression data from Genotype-Tissue Expression and eQTLGen, along with protein level data from deCODE and UK Biobank Pharma Proteomics Project, were examined in relation to pneumoconiosis data from FinnGen. To validate our findings, we assessed self-measured gut flora from a pneumoconiosis cohort and performed fine mapping, drug prediction, molecular docking, and Phenome-Wide Association Studies to explore relevant phenotypes of key genes. RESULTS: Three core gut microorganisms were identified: Romboutsia ( OR = 0.249) as a protective factor against silicosis, Pasteurellaceae ( OR = 3.207) and Haemophilus parainfluenzae ( OR = 2.343) as risk factors for inorganic pneumoconiosis. Additionally, mapping and quantitative trait loci analyses revealed that the genes VIM, STX8, and MIF were significantly associated with pneumoconiosis risk. CONCLUSIONS This multi-omics study highlights the associations between gut microbiota and key genes ( VIM, STX8, MIF) with pneumoconiosis, offering insights into potential therapeutic targets and personalized treatment strategies.
Humans ; Male ; East Asian People/genetics* ; Europe ; Gastrointestinal Microbiome ; Lung ; Macrophage Migration-Inhibitory Factors/metabolism* ; Mendelian Randomization Analysis ; Multiomics ; Pneumoconiosis/microbiology* ; Intramolecular Oxidoreductases